Relative Energy Deficiency in sport is experiencing remarkable popularity of late, particularly among female athletes. This condition is underpinned by low energy availability, which is a byproduct of high energy expenditure, inadequate energy intake, or a combination of the two. Several contributing factors exist that may predispose an athlete to low energy availability, and therefore a holistic and comprehensive assessment may be required to identify the root causes. The focus of the current narrative review is to discuss the primary contributing factors as well as known risk factors for low energy availability among female athletes to help practitioners increase awareness on the topic and identify future areas of focus.

Sport nutrition knowledge has been shown to influence dietary habits of athletes. The purpose of the current study was to examine relationships between sport nutrition knowledge and body composition and examine potential predictors of body weight goals in collegiate athletes. Participants included National Collegiate Athletic Association Division III women (n = 42, height: 169.9 ± 6.9 cm; body mass: 67.1 ± 8.6 kg; fat-free mass: 51.3 ± 6.6 kg; body fat percent: 24.2 ± 5.3%) and men (n = 25, height: 180.8 ± 7.2 cm; body mass: 89.2 ± 20.5 kg; fat-free mass: 75.9 ± 12.2 kg; body fat percent: 13.5 ± 8.9%) athletes. Body composition was assessed via air displacement plethysmography. Athletes completed a validated questionnaire designed to assess sport nutrition knowledge and were asked questions about their perceived dietary energy and macronutrient requirements, as well as their body weight goal (i.e., lose, maintain, gain weight). Athletes answered 47.98 ± 11.29% of questions correctly on the nutrition questionnaire with no differences observed between sexes (men: 49.52 ± 11.76% vs. women: 47.03 ± 11.04%; p = 0.40). An inverse relationship between sport nutrition knowledge scores and body fat percentage (BF%) (r = −0.330; p = 0.008), and fat mass (r = −0.268; p = 0.032) was observed for all athletes. Fat mass (β = 0.224), BF% (β = 0.217), and body mass index (BMI) (β = 0.421) were all significant (p < 0.05) predictors of body weight goal in women. All athletes significantly (p < 0.001) underestimated daily energy (−1360 ± 610.2 kcal/day), carbohydrate (−301.6 ± 149.2 grams/day [g/day]), and fat (−41.4 ± 34.5 g/day) requirements. Division III collegiate athletes have a low level of sport nutrition knowledge, which was associated with a higher BF%. Women athletes with a higher body weight, BF% and BMI were more likely to select weight loss as a body weight goal. Athletes also significantly underestimated their energy and carbohydrate requirements based upon the demands of their sport, independent of sex.

Young athletes may be at risk for low energy availability (LEA) or dietary habits that are indicative of eating disorders. Thus, the purpose of the current study was to investigate the prevalence of LEA among high school athletes and examine those at risk for eating disorders. A secondary aim was to examine relationships between sport nutrition knowledge, body composition, and LEA. Methods: 94 male (n = 42) and female (n = 52) mean ± SD age: 18.09 ± 2.44 y; height: 172.6 ± 9.8 cm; body mass: 68.7 ± 14.5 kg; BMI: 22.91 ± 3.3 kg·m⁻²) athletes completed a body composition assessment and electronic versions of the abridged sports nutrition knowledge questionnaire (ASNK-Q), brief eating disorder in athletes questionnaire (BEDA-Q), and the low energy availability for females questionnaire (LEAF-Q; females only). Results: 52.1% of female athletes were classified as being at risk for LEA. Moderate inverse relationships existed for computed LEAF-Q scores and BMI (r = −0.394; p < 0.01). A total of 42.9% of males (n = 18) and 68.6% of females (n = 35) were at risk for eating disorders, with females being at greater risk (p < 0.01). Body fat percentage was a predictor (β = −0.095; p = −0.01) for eating disorder risk status. For every 1 unit increase in body fat percentage, athletes were 0.909 (95% CI: 0.845–0.977) times less likely to be classified as at risk for an eating disorder. Male (46.5 ± 13.9) and female (46.9 ± 11.4) athletes scored poorly on the ASNK-Q, with no differences between sex (p = 0.895). Conclusions: Female athletes were at a greater risk for eating disorders. No relationships existed between sport nutrition knowledge and %BF. Female athletes with a higher %BF had a lower risk for an eating disorder and risk for LEA.

(1) Background: Limited information exists on the prevalence of low energy availability (LEA) in collegiate team sports. The purpose of this study was to examine the prevalence of LEA in collegiate women soccer players. (2) Methods: Collegiate women soccer athletes (n = 18, height: 1.67 ± 0.05 m; body mass: 65.3 ± 7.9 kg; body fat %: 24.9 ± 5.6%) had their body composition and sport nutrition knowledge assessed in the pre-season. Energy availability was assessed mid-season using a 4-day dietary log and activity energy expenditure values from a team-based monitoring system. A validated screening tool was used to screen for LEA. (3) Results: The screening tool classified 56.3% of athletes as at risk of LEA (<30 kcal/kg of FFM); however, the actual dietary intake identified 67% as LEA. Athletes identified as non-LEA consumed significantly more absolute (p = 0.040) and relative (p = 0.004) energy than LEA athletes. (4) Conclusions: There was a high prevalence of LEA among collegiate women soccer athletes. Although previously validated in women endurance athletes, the LEA screening tool was not effective in identifying those at risk of LEA in this sample of athletes.

Laboratory assessments of maximal oxygen uptake (VO_2max) are considered the “gold standard” for ascertaining cardiovascular fitness, but they are not always practical for use in team sport settings. Therefore, the purpose of the current study was to compare the criterion assessment of VO_2max on a treadmill to the progressive, multistage 20-m shuttle run test (i.e., Beep test), and to determine the predictability of 6 previously established Beep test predictive equations (i.e., Chatterjee, Flouris, Leger, Leger and Gadoury, Ramsbottom, St. Clair-Gibson). Collegiate women field hockey athletes (n = 65, mean±SD: age 19.6 ± 1.2 years; weight 64.7 ± 6.1 kg) completed criterion VO_2max (mean ± SD: 46.4 ± 4.6 mL·kg⁻¹·min⁻¹) and Beep tests to volitional fatigue. According to Bland–Altman and Ordinary Least Products Regressions, the Ramsbottom (46.5 ± 4.2 mL·kg⁻¹·min⁻¹) and Flouris (46.3 ± 3.8 mL·kg⁻¹·min⁻¹) equations were considered valid predictions of criterion measured VO_2max (46.4 ± 4.6). The Chatterjee, Leger, Leger and Gadoury, and St. Clair-Gibson equations overestimated VO_2max, and are not recommended for use with women collegiate field hockey athletes. The Ramsbottom and Flouris estimates of VO_2max from 20-m shuttle performances may be used in this population. For accurate estimates of VO_2max, the clientele’s age, fitness level, and training history should be considered when selecting equations.

Introduction: Benefits of protein consumption are established, yet athletes often consume insufficient protein. The effect of protein supplementation timing on self- reported wellness measures (SRWM) is unknown. The purpose was to examine the effect of protein supplementation timing on overall protein intake and SRWM. Methods: Collegiate athletes (men: n=13; body mass: 76.1 ± 6.6 kg; body fat %: 14.8 ± 2.3%) (women: n=16; body mass: 72.5 ± 10.8 kg; body fat %: 24.9 ± 4.6%), defined as protein-insufficient (daily intake <1.5 g/kg body weight) participated. Protein supplementation occurred over two 2-week periods (morning, evening) separated by a 2-week washout. Daily SRWM (fatigue, soreness, sleep, stress, mood, energy, recovery, satiety) were collected. ANOVA assessed differences in total protein intake and SRWM measures across conditions. Spearman correlations assessed relationships between protein intake and SRWM.Results: No sex difference existed in protein intake based on supplementation timing. Compared to baseline, morning and evening supplementation led to an increase (p<0.05) in absolute and relative protein intake for men and women. Satiety was increased during morning and evening conditions compared to washout for men (p=0.004) and women (p=0.012), but other SRWM did not differ. Correlations existed for relative protein intake and satiety (r=0.499, p<0.001) and stress (r=-0.321, p=0.019).Conclusions: Protein supplementation enabled participants to achieve the recommended protein intake and provided a greater feeling of satiety. Satiety did not differ between morning and evening, providing flexibility as to when to ingest a daily supplement.